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Wang L, Fu D, Weng S, Xu H, Liu L, Guo C, Ren Y, Liu Z, Han X. Genome-scale CRISPR-Cas9 screening stratifies pancreatic cancer with distinct outcomes and immunotherapeutic efficacy. Cell Signal 2023; 110:110811. [PMID: 37468054 DOI: 10.1016/j.cellsig.2023.110811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/02/2023] [Accepted: 07/15/2023] [Indexed: 07/21/2023]
Abstract
Pancreatic cancer (PC) was featured by dramatic heterogeneity and dismal outcomes. An ideal classification strategy capable of achieving risk stratification and individualized treatment is urgently needed to significantly improve prognosis. In this study, using the 105 prognostic cancer essential genes identified by genome-scale CRISPR-Cas9 screening and univariate Cox analysis, we established and verified three heterogeneous subtypes via non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms in the TCGA-PAAD cohort (176 samples) and four multi-center cohorts (233 samples), respectively. Among them, C1 with the worst prognosis was enriched in immune-related pathways, possessed superior infiltration abundance of immune cells and immune checkpoint molecules expression, and might be most sensitive to immunotherapy. C3, owing a moderate prognosis, might be featured by proliferative biological function, and despite its highest immunogenicity, the defects in antigen processing and presentation ability coupled with barren immune environment render it ineffective for immunotherapy, while it had potential sensitivity to paclitaxel and methotrexate. Besides, C2 harbored the best prognosis and was characterized by metabolism-related functions. These results could deepen our understanding of PC molecular heterogeneity and provide a trustworthy reference for prognostic stratification management and precision medicine in clinical practice.
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Affiliation(s)
- Libo Wang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China; Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Deshuang Fu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China; Department of Dermatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Siyuan Weng
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Hui Xu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Long Liu
- Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Chunguang Guo
- Department of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Yuqing Ren
- Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China.
| | - Xinwei Han
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, Henan Province, China.
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Luo Q, Liu J, Fu Q, Zhang X, Yu P, Liu P, Zhang J, Tian H, Chen S, Zhang H, Qin T. Identifying cancer cell‐secreted proteins that activate cancer‐associated fibroblasts as prognostic factors for patients with pancreatic cancer. J Cell Mol Med 2022; 26:5657-5669. [DOI: 10.1111/jcmm.17596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 08/26/2022] [Accepted: 09/30/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Qiankun Luo
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
| | - Jiayin Liu
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
| | - Qiang Fu
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
| | - Xu Zhang
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
| | - Pengfei Yu
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
| | - Pan Liu
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
| | - Jiali Zhang
- Academy of Medical Sciences, Zhengzhou University Zhengzhou China
| | - Huiyuan Tian
- Department of Research and Discipline Development Henan Provincial People's Hospital, Zhengzhou University People's Hospital Zhengzhou China
| | - Song Chen
- Translational Research Institute, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, and Molecular Pathology Center Academy of Medical Sciences, Zhengzhou University Zhengzhou China
| | - Hongwei Zhang
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
- Henan University People's Hospital Zhengzhou China
| | - Tao Qin
- Department of Hepatobilliary and Pancreatic surgery Zhengzhou University People's Hospital, Henan Provincial People's Hospital Zhengzhou China
- Henan University People's Hospital Zhengzhou China
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3
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Lei D, Chen Y, Zhou Y, Hu G, Luo F. A Starvation-Based 9-mRNA Signature Correlates With Prognosis in Patients With Hepatocellular Carcinoma. Front Oncol 2021; 11:716757. [PMID: 34900672 PMCID: PMC8663092 DOI: 10.3389/fonc.2021.716757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 11/08/2021] [Indexed: 01/07/2023] Open
Abstract
Background Hepatocellular carcinoma (HCC) is one of the world’s most prevalent and lethal cancers. Notably, the microenvironment of tumor starvation is closely related to cancer malignancy. Our study constructed a signature of starvation-related genes to predict the prognosis of liver cancer patients. Methods The mRNA expression matrix and corresponding clinical information of HCC patients were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Gene set enrichment analysis (GSEA) was used to distinguish different genes in the hunger metabolism gene in liver cancer and adjacent tissues. Gene Set Enrichment Analysis (GSEA) was used to identify biological differences between high- and low-risk samples. Univariate and multivariate analyses were used to construct prognostic models for hunger-related genes. Kaplan-Meier (KM) and receiver-operating characteristic (ROC) were used to assess the model accuracy. The model and relevant clinical information were used to construct a nomogram, protein expression was detected by western blot (WB), and transwell assay was used to evaluate the invasive and metastatic ability of cells. Results First, we used univariate analysis to identify 35 prognostic genes, which were further demonstrated to be associated with starvation metabolism through Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). We then used multivariate analysis to build a model with nine genes. Finally, we divided the sample into low- and high-risk groups according to the median of the risk score. KM can be used to conclude that the prognosis of high- and low-risk samples is significantly different, and the prognosis of high-risk samples is worse. The prognostic accuracy of the 9-mRNA signature was also tested in the validation data set. GSEA was used to identify typical pathways and biological processes related to 9-mRNA, cell cycle, hypoxia, p53 pathway, and PI3K/AKT/mTOR pathway, as well as biological processes related to the model. As evidenced by WB, EIF2S1 expression was increased after starvation. Overall, EIF2S1 plays an important role in the invasion and metastasis of liver cancer. Conclusions The 9-mRNA model can serve as an accurate signature to predict the prognosis of liver cancer patients. However, its mechanism of action warrants further investigation.
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Affiliation(s)
- Dengliang Lei
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yue Chen
- Central Laboratory, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yang Zhou
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Gangli Hu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Fang Luo
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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Chen Q, Pu N, Yin H, Zhang J, Zhao G, Lou W, Wu W. A metabolism-relevant signature as a predictor for prognosis and therapeutic response in pancreatic cancer. Exp Biol Med (Maywood) 2021; 247:120-130. [PMID: 34632851 DOI: 10.1177/15353702211049220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Although several altered metabolic genes have been identified to be involved in the tumorigenesis and advance of pancreatic cancer (PC), their prognostic values remained unclear. The purpose of this study was to explore new targets and establish a metabolic signature to predict prognosis and chemotherapy response for optimal individualized treatment. The expression data of PC patients from two independent cohorts and metabolism-related genes from KEGG were utilized and analyzed for the establishment of the signature via lasso regression. Then, the differentially expressed candidate genes were further confirmed via online data mining platform and qRT-PCR of clinical specimens. Then, the analyses of gene set enrichment, mutation, and chemotherapeutic response were performed via R package. As results showed, 109 differentially expressed metabolic genes were screened out in PC. Then a metabolism-related five-gene signature comprising B3GNT3, BCAT1, KYNU, LDHA, and TYMS was constructed and showed excellent ability for predicting survival. A novel nomogram coordinating the metabolic signature and other independent prognostic parameters was developed and showed better predictive power in predicting survival. In addition, this metabolic signature was significantly involved in the activation of multiple oncological pathways and regulation of the tumor immune microenvironment. The patients with high risk scores had higher tumor mutation burdens and were prone to be more sensitive to chemotherapy. In summary, our work identified a new metabolic signature and established a superior prognostic nomogram which may supply more indications to explore novel strategies for diagnosis and treatment.
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Affiliation(s)
- Qiangda Chen
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Cancer Center, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Ning Pu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Cancer Center, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Hanlin Yin
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Cancer Center, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jicheng Zhang
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Cancer Center, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Guochao Zhao
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Cancer Center, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Wenhui Lou
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Cancer Center, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Wenchuan Wu
- Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China.,Cancer Center, Zhongshan Hospital, Fudan University, Shanghai 200032, China
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Katsuta E, Huyser M, Yan L, Takabe K. A prognostic score based on long-term survivor unique transcriptomic signatures predicts patient survival in pancreatic ductal adenocarcinoma. Am J Cancer Res 2021; 11:4294-4307. [PMID: 34659888 PMCID: PMC8493373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 07/19/2021] [Indexed: 06/13/2023] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is known for its poor prognosis with few long-term survivors. This study aimed to establish a prognostic score using unique transcriptomic profiles of long-term survivors to be used as a patient selection tool for meaningful clinical intervention in PDAC. In TCGA PDAC cohort, 16 genes were significantly upregulated in the long-term survivor tumors. A prognostic score was established using these 16 genes by LASSO Cox regression, and PHKG1, HOXA4, ISL2, DMRT3 and TRA2A gene expressions were included in the score. The prognostic value was confirmed in both testing and validation cohorts. The characteristics of the high score tumor was investigated by bioinformatical approach. The high score tumor was associated with TP53 mutation but not with other commonly enhanced signaling pathways in PDAC. The high score tumor was associated with higher tumor mutational burden and unfavorable tumor microenvironment (TME), such as lower infiltration of CD8-positive T cells and dendritic cells, and less cell composition of mature blood vessels and fibroblasts. The high score tumor was also associated with enhanced cell proliferation and margin positivity after surgery. The impact of score component genes on the cell proliferation was investigated by in vitro experiments. Silencing of the score component genes promoted cell proliferation. In conclusion, the prognostic score predicted PDAC patient survival and was associated with cancer aggressiveness such as unfavorable TME and enhanced cell proliferation.
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Affiliation(s)
- Eriko Katsuta
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer CenterBuffalo, NY, USA
| | - Michelle Huyser
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer CenterBuffalo, NY, USA
| | - Li Yan
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer CenterBuffalo, NY, USA
| | - Kazuaki Takabe
- Department of Surgical Oncology, Roswell Park Comprehensive Cancer CenterBuffalo, NY, USA
- Department of Surgery, University at Buffalo Jacobs School of Medicine and Biomedical Sciences, The State University of New YorkBuffalo, NY, USA
- Department of Breast Surgery and Oncology, Tokyo Medical UniversityTokyo, Japan
- Department of Surgery, Yokohama City UniversityYokohama, Japan
- Department of Surgery, Niigata University Graduate School of Medical and Dental SciencesNiigata, Japan
- Department of Breast Surgery, Fukushima Medical UniversityFukushima, Japan
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6
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Dong Y, Tian J, Yan B, Lv K, Li J, Fu D. Liver-Metastasis-Related Genes are Potential Biomarkers for Predicting the Clinical Outcomes of Patients with Pancreatic Adenocarcinoma. Pathol Oncol Res 2021; 27:1609822. [PMID: 34290570 PMCID: PMC8286999 DOI: 10.3389/pore.2021.1609822] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 06/21/2021] [Indexed: 12/26/2022]
Abstract
It is widely acknowledged that metastasis determines the prognosis of pancreatic adenocarcinoma (PAAD), and the liver is the most primary distant metastatic location of PAAD. It is worth exploring the value of liver-metastasis-related genetic prognostic signature (LM-PS) in predicting the clinical outcomes of PAAD patients post R0 resection. We collected 65 tumors and 165 normal pancreatic data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression project (GTEx), respectively. Differentially expressed genes (DEGs) between primary tumor and normal pancreatic samples were intersected with DEGs between primary tumor samples with liver metastasis and those without new tumor events. The intersected 45 genes were input into univariate Cox regression analysis to identify the prognostic genes. Thirty-three prognostic liver-metastasis-related genes were identified and included in least absolute shrinkage and selection operator (LASSO) analysis to develop a seven-gene LM-PS, which included six risk genes (ANO1, FAM83A, GPR87, ITGB6, KLK10, and SERPINE1) and one protective gene (SMIM32). The PAAD patients were grouped into low- and high-risk groups based on the median value of risk scores. The LM-PS harbored an independent predictive ability to distinguish patients with a high-risk of death and liver metastasis after R0 resection. Moreover, a robust prognostic nomogram based on LM-PS, the number of positive lymph nodes, and histologic grade were established to predict the overall survival of PAAD patients. Besides, a transcription factor‐microRNA coregulatory network was constructed for the seven LM-PS genes, and the immune infiltration and genomic alterations were systematically explored in the TGCA-PAAD cohort.
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Affiliation(s)
- Yinlei Dong
- Department of Pancreatic Surgery, Pancreatic Disease Institute, Huashan Hospital, Fudan University, Shanghai, China
| | - Junjie Tian
- Department of Urology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Bingqian Yan
- Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China
| | - Kun Lv
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ji Li
- Department of Pancreatic Surgery, Pancreatic Disease Institute, Huashan Hospital, Fudan University, Shanghai, China
| | - Deliang Fu
- Department of Pancreatic Surgery, Pancreatic Disease Institute, Huashan Hospital, Fudan University, Shanghai, China
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7
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Huo J, Wu L, Zang Y. Development and Validation of a Novel Metabolic-Related Signature Predicting Overall Survival for Pancreatic Cancer. Front Genet 2021; 12:561254. [PMID: 34122496 PMCID: PMC8194314 DOI: 10.3389/fgene.2021.561254] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 04/26/2021] [Indexed: 12/30/2022] Open
Abstract
Recently, growing evidence has revealed the significant effect of reprogrammed metabolism on pancreatic cancer in relation to carcinogenesis, progression, and treatment. However, the prognostic value of metabolism-related genes in pancreatic cancer has not been fully revealed. We identified 379 differentially expressed metabolic-related genes (DEMRGs) by comparing 178 pancreatic cancer tissues with 171 normal pancreatic tissues in The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression project (GTEx) databases. Then, we used univariate Cox regression analysis together with Lasso regression for constructing a prognostic model consisting of 15 metabolic genes. The unified risk score formula and cutoff value were taken into account to divide patients into two groups: high risk and low risk, with the former exhibiting a worse prognosis compared with the latter. The external validation results of the International Cancer Genome Consortium (IGCC) cohort and the Gene Expression Omnibus (GEO) cohort further confirm the effectiveness of this prognostic model. As shown in the receiver operating characteristic (ROC) curve, the area under curve (AUC) values of the risk score for overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were 0.871, 0.885, and 0.886, respectively. Based on the Gene Set Enrichment Analysis (GSEA), the 15-gene signature can affect some important biological processes and pathways of pancreatic cancer. In addition, the prognostic model was significantly correlated with the tumor immune microenvironment (immune cell infiltration, and immune checkpoint expression, etc.) and clinicopathological features (pathological stage, lymph node, and metastasis, etc.). We also built a nomogram based on three independent prognostic predictors (including individual neoplasm status, lymph node metastasis, and risk score) for the prediction of 1-, 3-, and 5-year OS of pancreatic cancer, which may help to further improve the treatment strategy of pancreatic cancer.
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Affiliation(s)
| | - Liqun Wu
- Liver Disease Center, The Affiliated Hospital of Qingdao University, Qingdao, China
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8
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Jie Y, Peng W, Li YY. Identification of novel candidate biomarkers for pancreatic adenocarcinoma based on TCGA cohort. Aging (Albany NY) 2021; 13:5698-5717. [PMID: 33591944 PMCID: PMC7950294 DOI: 10.18632/aging.202494] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 12/18/2020] [Indexed: 12/15/2022]
Abstract
Pancreatic adenocarcinoma (PAAD) is the most serious solid tumor type throughout the world. The present study aimed to identify novel biomarkers and potential efficacious small drugs in PAAD using integrated bioinformatics analyses. A total of 4777 differentially expressed genes (DEGs) were filtered, 2536 upregulated DEGs and 2241 downregulated DEGs. Weighted gene co-expression network analysis was then used and identified 12 modules, of which, blue module with the most significant enrichment result was selected. KEGG and GO enrichment analyses showed that all DEGs of blue module were enriched in EMT and PI3K/Akt pathway. Three hub genes (ITGB1, ITGB5, and OSMR) were determined as key genes with higher expression levels, significant prognostic value and excellent diagnostic efficiency for PAAD. Additionally, some small molecule drugs that possess the potential to treat PAAD were screened out, including thapsigargin (TG). Functional in vitro experiments revealed that TG repressed cell viability via inactivating the PI3K/Akt pathway in PAAD cells. Totally, our findings identified three key genes implicated in PAAD and screened out several potential small drugs to treat PAAD.
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Affiliation(s)
- Yang Jie
- Department of Pharmacy, Shandong Provincial Hospital, Jinan 250022, Shandong, P.R. China
| | - Wang Peng
- Department of Pharmacy, The First Affiliated Hospital of Shandong First Medical University, Jinan 250014, Shandong, P.R. China
| | - Yuan-Yuan Li
- Department of Pharmacy, The First Affiliated Hospital of Shandong First Medical University, Jinan 250014, Shandong, P.R. China
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9
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Luo L, Li Y, Huang C, Lin Y, Su Y, Cen H, Chen Y, Peng S, Ren T, Xie R, Zeng L. A new 7-gene survival score assay for pancreatic cancer patient prognosis prediction. Am J Cancer Res 2021; 11:495-512. [PMID: 33575083 PMCID: PMC7868749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Accepted: 12/18/2020] [Indexed: 06/12/2023] Open
Abstract
Gene expression features that are valuable for pancreatic ductal adenocarcinoma (PDAC) prognosis are still largely unknown. We aimed to explore pivotal molecular signatures for PDAC progression and establish an efficient survival score to predict PDAC prognosis. Overall, 163 overlapping genes were identified from three statistical methods, including differentially expressed genes (DEGs), coexpression network analysis (WGCNA), and target genes for miRNAs that were significantly related to PDAC patients' overall survival (OS). Then, according to the optimal value of the cross-validation curve (lambda = 0.031), 7 non-zero coefficients (ARNTL2, DSG3, PTPRR, ANLN, S100A14, ANKRD22, and TSPAN7) were selected to establish a prognostic prediction model of PDAC patients. We further confirmed the expression level of 7 genes using RT-PCR, western blot, and immunohistochemistry staining in PDAC patients' tissues. Our results showed that the ROC curve of the 7-mRNA model indicated good predictive ability for 1- and 2-year OS in three datasets (TCGA: 0.71, 0.69; ICGC: 0.8, 0.74; GEO batch: 0.61, 0.7, respectively). The hazard ratio (HR) of the low-risk group had a similar significant result (TCGA: HR = 0.3723; ICGC: HR = 0.2813; GEO batch: HR = 0.4999; all P < 0.001). Furthermore, Log-rank test results in three cohorts showed that the 7-mRNA assay excellently predicted the prognosis and metastasis, especially in TNM stage I&II subgroups of PDAC. In conclusion, the strong validation of our 7-mRNA signature indicates the promising effectiveness of its clinical application, especially in patients with TNM stages I&II.
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Affiliation(s)
- Lisi Luo
- Department of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Yufang Li
- Department of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Chumei Huang
- Department of Gastroenterology, The Seventh Affiliated Hospital of Sun Yat-sen UniversityShenzhen 518107, China
| | - Yujing Lin
- Department of Pathology, The Fifth Affiliated Hospital of Sun Yat-sen UniversityZhuhai, China
| | - Yonghui Su
- Department of General Surgery, The Fifth Affiliated Hospital of Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Hong Cen
- Department of General Surgery, The Fifth Affiliated Hospital of Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Yutong Chen
- Department of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Siqi Peng
- Center for Interventional Medicine, The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
- Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Tianyi Ren
- Department of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Rongzhi Xie
- Department of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
| | - Linjuan Zeng
- Department of Abdominal Oncology, The Cancer Center of The Fifth Affiliated Hospital, Sun Yat-sen UniversityZhuhai 519000, Guangdong Province, China
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10
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Feng Z, Shi M, Li K, Ma Y, Jiang L, Chen H, Peng C. Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma. J Transl Med 2020; 18:360. [PMID: 32958051 PMCID: PMC7507616 DOI: 10.1186/s12967-020-02527-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 09/15/2020] [Indexed: 02/07/2023] Open
Abstract
Background Cancer stem cells (CSCs) are crucial to the malignant behaviour and poor prognosis of pancreatic ductal adenocarcinoma (PDAC). In recent years, CSC biology has been widely studied, but practical prognostic signatures based on CSC-related genes have not been established or reported in PDAC. Methods A signature was developed and validated in seven independent PDAC datasets. The MTAB-6134 cohort was used as the training set, while one local Chinese cohort and five other public cohorts were used for external validation. CSC-related genes with credible prognostic roles were selected to form the signature, and their predictive performance was evaluated by Kaplan–Meier survival, receiver operating characteristic (ROC), and calibration curves. Correlation analysis was employed to clarify the potential biological characteristics of the gene signature. Results A robust signature comprising DCBLD2, GSDMD, PMAIP1, and PLOD2 was developed. It classified patients into high-risk and low-risk groups. High-risk patients had significantly shorter overall survival (OS) and disease-free survival (DFS) than low-risk patients. Calibration curves and Cox regression analysis demonstrated powerful predictive performance. ROC curves showed the better survival prediction by this model than other models. Functional analysis revealed a positive association between risk score and CSC markers. These results had cross-dataset compatibility. Impact This signature could help further improve the current TNM staging system and provide data for the development of novel personalized therapeutic strategies in the future.
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Affiliation(s)
- Zengyu Feng
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Institute of Translational Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Minmin Shi
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Institute of Translational Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Kexian Li
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Institute of Translational Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yang Ma
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.,State Key Laboratory of Oncogenes and Related Genes, Institute of Translational Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Lingxi Jiang
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. .,State Key Laboratory of Oncogenes and Related Genes, Institute of Translational Medicine, Shanghai Jiaotong University, Shanghai, China.
| | - Hao Chen
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. .,State Key Laboratory of Oncogenes and Related Genes, Institute of Translational Medicine, Shanghai Jiaotong University, Shanghai, China.
| | - Chenghong Peng
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. .,State Key Laboratory of Oncogenes and Related Genes, Institute of Translational Medicine, Shanghai Jiaotong University, Shanghai, China.
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Yang J, Shi W, Zhu S, Yang C. Construction of a 6-gene prognostic signature to assess prognosis of patients with pancreatic cancer. Medicine (Baltimore) 2020; 99:e22092. [PMID: 32925750 PMCID: PMC7489722 DOI: 10.1097/md.0000000000022092] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Pancreatic cancer (PaCa) is one of the most fatal cancers in the world. Although great efforts have made to explore the mechanisms of PaCa oncogenesis, the prognosis of PaCa patients is still unsatisfactory. Thus, it is imperative to further understand the potential carcinogenesis of PaCa and reliable prognostic models.The gene expression profile and clinical information of GSE21501 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was applied to explore the potent genes associated with the overall survival (OS) events of PaCa patients. Cox regression model was applied to selecting prognostic genes and establish prognostic model. The prognostic values of six-gene signature were validated in TCGA-PAAD cohort.According to the WGCNA analysis, a total of 19 modules were identified and 115 hub genes in the mostly associated module were reserved for next analysis. According to the univariate and multivariate Cox regression analysis, we established a six-gene signature (FTSJ3, STAT1, STX2, CDX2, RASSF4, MACF1) which could effectively evaluate the overall survival (OS) of PaCa patients. In validated patients' cohorts, the six-gene signature exhibited excellent prognostic value in TCGA-PAAD cohort as well.We developed a six-gene signature to exactly predict OS of PaCa patients and provide a novel personalized strategy for evaluating prognosis. The findings may be contributed to medical customization and therapeutic decision in clinical practice.
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Affiliation(s)
| | | | | | - Cheng Yang
- Department of Gastroenterology, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi 214023, China
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Wu M, Li X, Liu R, Yuan H, Liu W, Liu Z. Development and validation of a metastasis-related Gene Signature for predicting the Overall Survival in patients with Pancreatic Ductal Adenocarcinoma. J Cancer 2020; 11:6299-6318. [PMID: 33033514 PMCID: PMC7532518 DOI: 10.7150/jca.47629] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 08/13/2020] [Indexed: 02/06/2023] Open
Abstract
Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal, aggressive cancer characterized by invasiveness and metastasis. In this study, we aimed to propose a gene prediction model based on metastasis-related genes (MTGs) to more accurately predict PDAC prognosis. Methods: Differentially expressed MTGs (DE-MTGs) were identified via integrated analysis of gene expression omnibus (GEO) datasets and Human Cancer Metastasis Database (HCMDB). Overall survival (OS) related DE-MTGs were then identified and a prognostic gene signature was established using Lasso-Cox regression with TCGA-PAAD datasets. Tumor immunity was analyzed using ESTIMATE and CIBERSORT algorithms. Finally, a nomogram predicting 1-year, 2-year, and 3-year OS of PDAC patients was established based on the prognostic gene signature and relevant clinical parameters using a stepwise Cox regression model. Results: A total of 36 DE-MTGs related to OS were identified in PDAC. Consequently, an MTG-based gene signature comprising of RACGAP1, RARRES3, TPX2, MMP28, GPR87, KIF14, and TSPAN7 was established to predict the OS of PDAC. The MTG-based gene signature was able to distinguish high-risk patients with significantly poorer prognosis and accurately predict OS of PDAC in both the training and external validation datasets. Cox regression analysis indicated that the MTG-based gene signature was an independent prognostic factor in PDAC. The gene set enrichment analysis (GSEA) showed that molecular alterations in the high-risk group were associated with multiple oncological pathways. Moreover, analysis of tumor immunity revealed significantly higher levels of follicular helper T cells and M0 macrophage infiltration, and lower levels of infiltrating naïve B cells, CD8 T cells, monocytes, and resting dendritic cells in the high-risk group. Immune cell infiltration levels were significantly associated with the expression of the seven DE-MTGs. Finally, a nomogram was established by incorporating the prognostic gene signature and clinical parameters, which was superior to the AJCC staging system in predicting the OS of PDAC patients. Conclusions: The DE-MTGs we identified were closely associated with the progress and prognosis of PDAC and are potential therapeutic targets. The MTG-based gene signature and nomogram may serve to improve the individualized prediction of survival, assisting in clinical decision-making.
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Affiliation(s)
- Mengwei Wu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xiaobin Li
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Rui Liu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Hongwei Yuan
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Wei Liu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ziwen Liu
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
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Identification of a 5-Gene Metabolic Signature for Predicting Prognosis Based on an Integrated Analysis of Tumor Microenvironment in Lung Adenocarcinoma. JOURNAL OF ONCOLOGY 2020; 2020:5310793. [PMID: 32684932 PMCID: PMC7335383 DOI: 10.1155/2020/5310793] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 05/08/2020] [Accepted: 05/25/2020] [Indexed: 12/21/2022]
Abstract
Lung adenocarcinoma (LUAD) is a common subtype of lung cancer with a depressing survival rate. The reprogramming of tumor metabolism was identified as a new hallmark of cancer in tumor microenvironment (TME), and we made a comprehensive exploration to reveal the prognostic role of the metabolic-related genes. Transcriptome profiling data of LUAD were, respectively, downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Based on the extracted metabolic-related genes, a novel 5-gene metabolic prognostic signature (including GNPNAT1, LPGAT1, TYMS, LDHA, and PTGES) was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. This signature confirmed its robustness and accuracy by external validation in multiple databases. It could be an independent risk factor for LUAD, and the nomograms possessed moderately accurate performance with the C-index of 0.755 (95% confidence interval: 0.706–0.804) and 0.691 (95% confidence interval: 0.636–0.746) in training set and testing set. This signature could reveal the metabolic features according to the results of gene set enrichment analysis (GSEA) and meanwhile monitor the status of TME through ESTIMATE scores and the infiltration levels of immune cells. In conclusion, this gene signature is a cost-effective tool which could indicate the status of TME to provide more clues in the exploration of new diagnostic and therapeutic strategy.
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